Feature Selection

Time series feature learning with labeled and unlabeled data
Time series classification has attracted much attention in the last two decades. However, in many real-world applications, the …
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Query-oriented citation recommendation based on network correlation
With the rapid proliferation of information technology, researchers find it more and more difficult to rapidly find appropriate …
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Task sensitive feature exploration and learning for multitask graph classification
Multitask learning (MTL) is commonly used for jointly optimizing multiple learning tasks. To date, all existing MTL methods have been …
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Multi-graph-view subgraph mining for graph classification
In this paper, we formulate a new multi-graph-view learning task, where each object to be classified contains graphs from multiple …
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Finding the best not the most: regularized loss minimization subgraph selection for graph classification
Classification on structure data, such as graphs, has drawn wide interest in recent years. Due to the lack of explicit features to …
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Multi-graph-view Learning for Graph Classification
Graph classification has traditionally focused on graphs generated from a single feature view. In many applications, it is common to …
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